Distinctive quantal properties of neurotransmission at excitatory and inhibitory autapses revealed using variance-mean analysis

Kaori Ikeda, Yuchio Yanagawa, John M. Bekkers

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    18 Citations (Scopus)

    Abstract

    Normal brain function depends on an interplay between glutamatergic and GABAergic synaptic transmission, yet questions remain about the biophysical differences between these two classes of synapse. By taking advantage of a simple culture system, we present here a detailed comparison of excitatory and inhibitory neurotransmission under identical conditions using the variance-mean (V-M) method of quantal analysis. First, we validate V-M analysis for glutamatergic autapses formed by isolated hippocampal pyramidal neurons in culture, confirming that the analysis accurately predicts the quantal amplitude (Q). We also show that V-M analysis is only weakly sensitive to intersite and intrasite quantal variance and to the known inhomogeneities in release probability (Pr). Next, by repeating the experiments with GABAergic autapses, we confirm that V-M analysis provides an accurate account of inhibitory neurotransmission in this system. Mean Pr, provided by V-M analysis, shows a dependence on extracellular Ca2+ concentration that is nearly identical for both excitatory and inhibitory autapses. Finally, the V-M method allows us to compare the locus of short-term synaptic plasticity at these connections. Glutamatergic autapses exhibit paired-pulse depression that depends mainly on changes in Pr, whereas depression at GABAergic autapses appears to depend primarily on changes in the number of release sites. We conclude that, apart from differences in the mechanisms of short-term plasticity, the basic quantal properties of excitatory and inhibitory connections in this hippocampal system are remarkably similar.

    Original languageEnglish
    Pages (from-to)13563-13573
    Number of pages11
    JournalJournal of Neuroscience
    Volume28
    Issue number50
    DOIs
    Publication statusPublished - 10 Dec 2008

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